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57 lines
2.0 KiB
Python
57 lines
2.0 KiB
Python
"""SQL agent."""
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from typing import Any, Dict, List, Optional
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from langchain.agents.agent import AgentExecutor
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from langchain.agents.agent_toolkits.sql.prompt import SQL_PREFIX, SQL_SUFFIX
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from langchain.agents.agent_toolkits.sql.toolkit import SQLDatabaseToolkit
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from langchain.agents.mrkl.base import ZeroShotAgent
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from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS
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from langchain.base_language import BaseLanguageModel
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from langchain.callbacks.base import BaseCallbackManager
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from langchain.chains.llm import LLMChain
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def create_sql_agent(
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llm: BaseLanguageModel,
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toolkit: SQLDatabaseToolkit,
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callback_manager: Optional[BaseCallbackManager] = None,
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prefix: str = SQL_PREFIX,
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suffix: str = SQL_SUFFIX,
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format_instructions: str = FORMAT_INSTRUCTIONS,
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input_variables: Optional[List[str]] = None,
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top_k: int = 10,
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max_iterations: Optional[int] = 15,
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max_execution_time: Optional[float] = None,
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early_stopping_method: str = "force",
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verbose: bool = False,
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agent_executor_kwargs: Optional[Dict[str, Any]] = None,
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**kwargs: Dict[str, Any],
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) -> AgentExecutor:
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"""Construct a sql agent from an LLM and tools."""
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tools = toolkit.get_tools()
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prefix = prefix.format(dialect=toolkit.dialect, top_k=top_k)
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prompt = ZeroShotAgent.create_prompt(
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tools,
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prefix=prefix,
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suffix=suffix,
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format_instructions=format_instructions,
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input_variables=input_variables,
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)
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llm_chain = LLMChain(
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llm=llm,
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prompt=prompt,
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callback_manager=callback_manager,
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)
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tool_names = [tool.name for tool in tools]
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agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs)
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return AgentExecutor.from_agent_and_tools(
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agent=agent,
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tools=tools,
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callback_manager=callback_manager,
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verbose=verbose,
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max_iterations=max_iterations,
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max_execution_time=max_execution_time,
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early_stopping_method=early_stopping_method,
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**(agent_executor_kwargs or {}),
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)
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